Xinwen Long
Papers
1
Total Citations
15
H-Index
1
About
Xinwen Long is a researcher whose work bridges information science and evaluation methodology, with a primary focus on enhancing decision-making frameworks in academic and technological domains. Their most notable contribution is the development of coordinated TOPSIS, an innovative refinement of the widely used TOPSIS evaluation method. In their highly cited 2018 paper, Long addressed a critical gap in traditional TOPSIS by incorporating indicator coordination, thereby offering a more nuanced and robust assessment tool. This methodological advancement has been applied to the evaluation of robotics academic journals, demonstrating its practical utility in scientometrics and research assessment. With 15 citations on this seminal work, Long’s research has influenced how scholars approach multi-criteria decision-making in complex fields. Their work is particularly valuable for students and researchers seeking to understand how evaluation metrics can be improved to reflect the interconnected nature of performance indicators. By advancing the theoretical foundations of coordinated TOPSIS, Xinwen Long has made a meaningful contribution to the toolkit available for rigorous academic and technological evaluation.
Research Focus
Key Achievements
Top Papers
- 1